ProgressiveGAN
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- NVIDIA
- Organisation type
- Industry
- Country
- United States of America
- Published
- 27 October 2017
- Authors
- Tero Karras, Timo Aila, Samuli Laine, Jaakko Lehtinen
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Image generation
- Numerical format
- FP32
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Highly cited
- Record confidence
- Unknown
- Citations
- 8,487
Sources
Where this record came from and when it was last checked.
- Reference
- Progressive Growing of GANs for Improved Quality, Stability, and Variation
- Last updated
- 25 May 2026
What the numbers mean
About this model
ProgressiveGAN was published by NVIDIA, in United States of America, in October 2017. The organisation is categorised as industry.
It works in Vision, and is recorded as doing image generation.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
The reason it appears in this catalogue at all is highly cited.
Answers
ProgressiveGAN — common questions
How many parameters does ProgressiveGAN have?
No parameter count has been published for ProgressiveGAN, which is why no memory or speed figure appears on this page.
Who created ProgressiveGAN?
ProgressiveGAN was published by NVIDIA, based in United States of America, categorised as industry.
When was ProgressiveGAN released?
ProgressiveGAN was published in October 2017. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is ProgressiveGAN used for?
ProgressiveGAN works in Vision, and is recorded as handling image generation. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
What GPU do I need to run ProgressiveGAN?
None. ProgressiveGAN is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is ProgressiveGAN open source?
The licensing for ProgressiveGAN was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.